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  • 1
    Online Resource
    Online Resource
    Stichting OpenAccess Foundation ; 2021
    In:  Research in Urbanism Series Vol. 7 ( 2021-02-18), p. 223-240
    In: Research in Urbanism Series, Stichting OpenAccess Foundation, Vol. 7 ( 2021-02-18), p. 223-240
    Abstract: A common measure to mitigate erosion along sandy beaches is the implementation of sand nourishments. The design and societal acceptance of such a soft mitigation measure demands information on the expected evolution at various time scales ranging from a storm event to multiple decades. Process-based morphodynamic models are increasingly applied to obtain detailed information on temporal behaviour. This paper discusses the process-based morphodynamic model applied to the Sand Motor and how the morphodynamic forecasts have benefitted from the findings of an interdisciplinary research program called NatureCoast. The starting point is the morphodynamic prediction of the Sand Motor made for an Environmental Impact Assessment in 2008 before construction began. After the construction, the model computations were optimized using the first-year field measurements and insights by applying advanced model features. Next, an integrated model was developed that seamlessly predicts the morphodynamics in both the subaqueous and subaerial domains of the Sand Motor. Decadal predictions illustrate the need to be able to resolve the marine and aeolian processes simultaneously in one modelling framework in the case of dynamic coastal landscapes. Finally, a novel morphodynamic acceleration technique was developed that allows for predicting the morphodynamics for multiple decades while incorporating storm events in one simulation. Combining the above-mentioned developments has led to a unique, open-source, process-based landscape tool for (complex) coastal sandy systems, which can stimulate further collaboration between research communities. Moreover, this work demonstrates the evolution from mono- to interdisciplinary forecasts of coastal evolution.
    Type of Medium: Online Resource
    ISSN: 1879-8217 , 1875-0192
    Language: Unknown
    Publisher: Stichting OpenAccess Foundation
    Publication Date: 2021
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  • 2
    Online Resource
    Online Resource
    Coastal Engineering Research Council ; 2023
    In:  Coastal Engineering Proceedings , No. 37 ( 2023-09-01), p. 22-
    In: Coastal Engineering Proceedings, Coastal Engineering Research Council, , No. 37 ( 2023-09-01), p. 22-
    Abstract: The availability of public satellite imagery, combined with advanced image processing, machine learning and cloud computing, triggered an unprecedented flow of information relevant to the coastal engineering community. From satellite imagery we can nowadays for example derive subtidal bathymetry, beach slopes, beach sediment types and coastline dynamics, at accuracies that increasingly allow for engineering applications. Regarding the latter two, global datasets on the occurrence of sandy beaches and historic shorelines have recently become available (Luijendijk et al., 2018). The high spatial and temporal resolution of this information yields more comprehensive understanding of our coasts and its dynamics (see Figure 1). This is not only of great added value in data-poor environments, it will also allow for more cost-effective coastal monitoring in data rich environments as the necessity of in-situ measurements will reduce in future. In this study we will expose the main drivers for coastal change for sandy and muddy coasts using satellite-derived shoreline (SDS) and machine learning algorithms.
    Type of Medium: Online Resource
    ISSN: 2156-1028 , 0589-087X
    Language: Unknown
    Publisher: Coastal Engineering Research Council
    Publication Date: 2023
    detail.hit.zdb_id: 2628774-2
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  • 3
    Online Resource
    Online Resource
    Coastal Engineering Research Council ; 2023
    In:  Coastal Engineering Proceedings , No. 37 ( 2023-09-01), p. 81-
    In: Coastal Engineering Proceedings, Coastal Engineering Research Council, , No. 37 ( 2023-09-01), p. 81-
    Abstract: Sea turtles are an important part of marine and coastal ecosystems around the world. Yet, six of seven sea turtle species are endangered (IUCN, 2021). While they spend most of their lives at sea, female turtles use sandy beaches as nesting habitat, where they dig their nests in the sand to incubate for up to two months. A major challenge to sea turtles is the degradation of their nesting beaches due to anthropogenic climate-change effects, such as accelerated sea level rise (SLR) and anomalous storm activity. While it is still uncertain how sandy beaches will respond to SLR, beaches backed by hard structures cannot migrate landward, leading to ‘coastal squeeze’—the erosion and consequential narrowing of beaches. Increased storm activity may lead to persistently high water levels at nesting beaches, resulting in the flooding or even erosion of incubating nests. Moreover, beach erosion during storms can bury nests under excessive sand and limit beach access through the formation of scarps. Nature-based solutions—for example in the form of turtle-friendly design of beaches along new land reclamations or by adding coastal vegetation or reefs to limit runup and reduce erosion on existing beaches—may offer promising opportunities to preserve and even expand global habitats for turtle nesting.
    Type of Medium: Online Resource
    ISSN: 2156-1028 , 0589-087X
    Language: Unknown
    Publisher: Coastal Engineering Research Council
    Publication Date: 2023
    detail.hit.zdb_id: 2628774-2
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  • 4
    In: Estuarine, Coastal and Shelf Science, Elsevier BV, Vol. 246 ( 2020-11), p. 107018-
    Type of Medium: Online Resource
    ISSN: 0272-7714
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 1466742-3
    detail.hit.zdb_id: 763369-5
    SSG: 21,3
    SSG: 12
    SSG: 14
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  Journal of Environmental Management Vol. 311 ( 2022-06), p. 114824-
    In: Journal of Environmental Management, Elsevier BV, Vol. 311 ( 2022-06), p. 114824-
    Type of Medium: Online Resource
    ISSN: 0301-4797
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 1469206-5
    SSG: 12
    SSG: 14
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  • 6
    In: Remote Sensing, MDPI AG, Vol. 13, No. 5 ( 2021-03-03), p. 934-
    Abstract: Forecasting shoreline evolution for sandy coasts is important for sustainable coastal management, given the present-day increasing anthropogenic pressures and a changing future climate. Here, we evaluate eight different time-series forecasting methods for predicting future shorelines derived from historic satellite-derived shorelines. Analyzing more than 37,000 transects around the globe, we find that traditional forecast methods altogether with some of the evaluated probabilistic Machine Learning (ML) time-series forecast algorithms, outperform Ordinary Least Squares (OLS) predictions for the majority of the sites. When forecasting seven years ahead, we find that these algorithms generate better predictions than OLS for 54% of the transect sites, producing forecasts with, on average, 29% smaller Mean Squared Error (MSE). Importantly, this advantage is shown to exist over all considered forecast horizons, i.e., from 1 up to 11 years. Although the ML algorithms do not produce significantly better predictions than traditional time-series forecast methods, some proved to be significantly more efficient in terms of computation time. We further provide insight in how these ML algorithms can be improved so that they can be expected to outperform not only OLS regression, but also the traditional time-series forecast methods. These forecasting algorithms can be used by coastal engineers, managers, and scientists to generate future shoreline prediction at a global level and derive conclusions thereof.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 7
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Marine Science Vol. 8 ( 2022-1-5)
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 8 ( 2022-1-5)
    Abstract: The Saudi Arabian tourism sector is growing, and its economy has flourished over the last decades. This has resulted in numerous coastal developments close to large economic centers, while many more are proposed or planned. The coastal developments have influenced the behavior of the shoreline in the past. Here we undertake a national assessment on the state of the coast of Saudi Arabia based on recent data sets on historic and future shoreline positions. While at national scale the shoreline is found to be stable over the last three decades, the Red Sea coast shows a regional-mean retreat rate while the Gulf coast shows a regional-mean prograding behavior. Detailed analysis of the temporal evolution of shoreline position at selected locations show that human interventions may have accelerated shoreline retreat along adjacent shorelines, some of which are Marine Protected Areas. Furthermore, reef-fronted coastal sections have a mean accretive shoreline change rate, while the open coast shows a mean retreat rate. Future shoreline projections under RCP 4.5 and RCP 8.5 show that large parts of the shoreline may experience an accelerated retreat or a change in its regime from either stable or sprograding to retreating. Under the high emission RCP 8.5 scenario, the length of coastline projected to retreat more than doubles along the Red Sea coast, and approximately triples along the Gulf coast in 2100. At national scale, the Saudi Arabian coastline is projected to experience regional-mean retreats of ~30 m and of ~130 m by 2050 and 2100 under both RCPs considered in this study. These results indicate that effective adaptation strategies will be required to protect areas of ecological and economic value, and that climate resilience should be a key consideration in planned or proposed coastal interventions.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2757748-X
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  • 8
    Online Resource
    Online Resource
    Frontiers Media SA ; 2021
    In:  Frontiers in Marine Science Vol. 8 ( 2021-5-24)
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 8 ( 2021-5-24)
    Abstract: The Sand Motor is a very large (20 million m 3 ) nourishment constructed along the coast in The Netherlands. The huge volume of sand is redistributed along the coast by natural forces stemming from tidal currents and waves. For environmental evaluation of this large construction, the benthic subtidal fauna has been sampled prior to the construction of the Sand Motor, and at 1, 2, 4, and 6 years after construction. Although some significant differences between years were detected, overall the total density, total biomass and average number of species per sample were surprisingly constant over this time period. However, large differences were found in the species accumulation curves over samples, and in the rank-biomass and rank-abundance plots. These were related to two important trends in the communities. First, the invasive mollusk Ensis leei , the biomass dominant in the years before construction of the Sand Motor, dwindled in importance in later years. Recruitment of the species failed, but it is unclear whether, and how, this is related to the construction of the Sand Motor. Second, the correlation structure between depth, grain size, bottom shear stress due to waves and currents, which is very tight along a linear coast, was disrupted by the Sand Motor. The community composition was shown to depend strongly on these physical factors. The nature of the dependencies did not change, but the range of different combinations of factors after construction of the Sand Motor was widely larger than before. Although samples had similar number of species per sample before and after construction, the average difference between samples after construction was much larger than before. The Sand Motor is a very large construction, leading to loss of a substantial area (order 100 ha) of submarine area, which recovers at a long time scale. Total disturbance of benthos by burial, expressed as area ∗ (time before full recovery) was shown to be similar for the Sand Motor and for other coastal nourishment schemes when expressed per unit volume of sediment applied. However, in contrast to beach and shoreface nourishments, the Sand Motor led to a habitat diversification in the coastal zone.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2757748-X
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  • 9
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2023-03-13)
    Abstract: Marine plastic pollution poses a potential threat to the ecosystem, but the sources and their magnitudes remain largely unclear. Existing bottom-up emission inventories vary among studies for two to three orders of magnitudes (OMs). Here, we adopt a top-down approach that uses observed dataset of sea surface plastic concentrations and an ensemble of ocean transport models to reduce the uncertainty of global plastic discharge. The optimal estimation of plastic emissions in this study varies about 1.5 OMs: 0.70 (0.13–3.8 as a 95% confidence interval) million metric tons yr −1 at the present day. We find that the variability of surface plastic abundance caused by different emission inventories is higher than that caused by model parameters. We suggest that more accurate emission inventories, more data for the abundance in the seawater and other compartments, and more accurate model parameters are required to further reduce the uncertainty of our estimate.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2553671-0
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  • 10
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  Water Vol. 13, No. 7 ( 2021-04-01), p. 976-
    In: Water, MDPI AG, Vol. 13, No. 7 ( 2021-04-01), p. 976-
    Abstract: There is a growing scientific and engineering interest in exploring how natural processes can provide management solutions to resolve the degradation and vulnerability of coastal environments [...]
    Type of Medium: Online Resource
    ISSN: 2073-4441
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2521238-2
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